| The role of artificial intelligence in achieving the Sustainable Development Goals R Vinuesa, H Azizpour, I Leite, M Balaam, V Dignum, S Domisch, ... Nature communications 11 (1), 1-10, 2020 | 1365 | 2020 |
| Enhancing computational fluid dynamics with machine learning R Vinuesa, SL Brunton Nature Computational Science 2 (6), 358-366, 2022 | 226* | 2022 |
| Predictions of turbulent shear flows using deep neural networks PA Srinivasan, L Guastoni, H Azizpour, P Schlatter, R Vinuesa Physical Review Fluids 4 (5), 054603, 2019 | 203 | 2019 |
| Convolutional-network models to predict wall-bounded turbulence from wall quantities L Guastoni, A Güemes, A Ianiro, S Discetti, P Schlatter, H Azizpour, ... Journal of Fluid Mechanics 928, A27, 2021 | 168* | 2021 |
| History effects and near equilibrium in adverse-pressure-gradient turbulent boundary layers A Bobke, R Vinuesa, R Örlü, P Schlatter J. Fluid Mech 820, 667-692, 2017 | 142 | 2017 |
| Aspect ratio effects in turbulent duct flows studied through direct numerical simulation R Vinuesa, A Noorani, A Lozano-Durán, GKE Khoury, P Schlatter, ... Journal of Turbulence 15 (10), 677-706, 2014 | 137 | 2014 |
| Turbulent boundary layers around wing sections up to Rec= 1,000,000 R Vinuesa, PS Negi, M Atzori, A Hanifi, DS Henningson, P Schlatter International Journal of Heat and Fluid Flow 72, 86-99, 2018 | 133 | 2018 |
| Direct numerical simulation of the flow around a wing section at moderate Reynolds number SM Hosseini, R Vinuesa, P Schlatter, A Hanifi, DS Henningson International Journal of Heat and Fluid Flow 61, 117-128, 2016 | 132 | 2016 |
| Physics-informed neural networks for solving Reynolds-averaged Navier–Stokes equations H Eivazi, M Tahani, P Schlatter, R Vinuesa Physics of Fluids 34 (7), 2022 | 129 | 2022 |
| On determining characteristic length scales in pressure-gradient turbulent boundary layers R Vinuesa, A Bobke, R Örlü, P Schlatter Physics of fluids 28 (5), 2016 | 110 | 2016 |
| COVID-19 digital contact tracing applications and techniques: A review post initial deployments M Shahroz, F Ahmad, MS Younis, N Ahmad, MNK Boulos, R Vinuesa, ... Transportation Engineering 5, 100072, 2021 | 103 | 2021 |
| Obtaining accurate mean velocity measurements in high Reynolds number turbulent boundary layers using Pitot tubes SCC Bailey, M Hultmark, JP Monty, PH Alfredsson, MS Chong, ... Journal of Fluid Mechanics 715, 642-670, 2013 | 102 | 2013 |
| From coarse wall measurements to turbulent velocity fields through deep learning A Güemes, S Discetti, A Ianiro, B Sirmacek, H Azizpour, R Vinuesa Physics of Fluids 33 (7), 2021 | 97 | 2021 |
| Secondary flow in turbulent ducts with increasing aspect ratio R Vinuesa, P Schlatter, HM Nagib Physical Review Fluids 3 (5), 054606, 2018 | 97* | 2018 |
| Convergence of numerical simulations of turbulent wall-bounded flows and mean cross-flow structure of rectangular ducts R Vinuesa, C Prus, P Schlatter, HM Nagib Meccanica 51, 3025-3042, 2016 | 93 | 2016 |
| An interpretable framework of data-driven turbulence modeling using deep neural networks C Jiang, R Vinuesa, R Chen, J Mi, S Laima, H Li Physics of Fluids 33 (5), 2021 | 92 | 2021 |
| Direct numerical simulation of the flow around a wall-mounted square cylinder under various inflow conditions R Vinuesa, P Schlatter, J Malm, C Mavriplis, DS Henningson Journal of Turbulence 16 (6), 555-587, 2015 | 77 | 2015 |
| Adverse-pressure-gradient effects on turbulent boundary layers: statistics and flow-field organization C Sanmiguel Vila, R Örlü, R Vinuesa, P Schlatter, A Ianiro, S Discetti Flow, turbulence and combustion 99, 589-612, 2017 | 73 | 2017 |
| Towards extraction of orthogonal and parsimonious non-linear modes from turbulent flows H Eivazi, S Le Clainche, S Hoyas, R Vinuesa Expert Systems with Applications 202, 117038, 2022 | 72 | 2022 |
| On the identification of well-behaved turbulent boundary layers CS Vila, R Vinuesa, S Discetti, A Ianiro, P Schlatter, R Örlü Journal of Fluid Mechanics 822, 109-138, 2017 | 72 | 2017 |
Hassan NagibIllinois Institute of Technology, Chicago, IL 60616Verified email at iit.edu
